Modern gas turbines for power generation and industrial applications and for aircraft propulsion systems generally comprise multistage axial compressors which are subject to multiple wear, contamination and other damage mechanisms during operation, which adversely affect the operation of the compressor. Timely identification of such machine states which deviate from the normal state forms an essential precondition for carrying out precautionary maintenance measures in order to prevent both critical operating states and unacceptable wear.
Clear classification and quantification of wear and damage are particularly important for diagnosis and monitoring of modern gas turbines. In particular, it is desirable in the case of gas turbines with multistage axial compressors to be able to indicate precisely the compressor stage in which the wear or damage feature has occurred, and how severely and how widely the damage has progressed with respect to a defined limit value. A further aim is to carry out diagnosis and monitoring processes for gas turbines during normal operation, without having to shut down the turbine.
Various diagnosis and monitoring methods for turbines are known from the prior art. By way of example, DE 40 12 278 A1 discloses a state diagnosis system for a steam turbine installation having a neural network model. With the aid of the model, the system can learn a plurality of information patterns, relating to oscillations that are dependent on the operating state, in advance, in order to produce an output signal, which indicates the operating state, when these occur. Waveforms of mechanical or acoustic oscillations, vibrations or electromagnetic oscillations are used and processed for this purpose.
In addition, a quality or classification subdivision is known from US 2002/0013664 A1 for monitoring rotating components on the basis of machine states. In this case, pressure pulsations of compressor air may be used as one of the possible input variables. A further method is known from U.S. Pat. No. 7,027,953 B2.
These methods, for example that in U.S. Pat. No. 7,027,953 B2, in which pressure sensors are used for each compressor stage to be observed, require a very high degree of instrumentation in the form of a large number of sensors, and they can detect only serious damage, for example the loss of a blade. Furthermore, methods such as these cannot precisely associate the damage with one compressor stage when using gas turbines with multistage axial compressors.